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In islanding microgrids (MGs), distributed generation units are in charge of controlling voltage, frequency, and current of the grid on their own without any assistance from the main grid. Therefore, it is of utmost importance to select and design a controller that is robust against disturbances and load variations. In this study, a new sliding mode controller with a rotating reference voltage algorithm is proposed that improves the load sharing between distributed generators (DGs) in an islanded mode MG. In the proposed algorithm, in order to improve the performance and convergence rate of the controller, the amplitude of the reference voltage signal of the controller is adaptively modified. As a case study, the proposed strategy is studied based on the assumption that there are three DGs in the grid. One of the DGs is in charge of regulating voltage and frequency based on a reference signal, and the two other DGs are responsible for load sharing and loads the current control mode. The MG under study consists of three low-voltage distributed generation units operating in parallel mode. In order to have a realistic case study, it is assumed that the MG consists of different types of loads such as balanced/unbalanced resistive, inductive, and nonlinear loads. The extensive simulations are applied to indicate that the proposed framework is able to provide more desirable total harmonic distortion (THD), lower steady-state error, and faster response compared with classic sliding mode controllers. [ABSTRACT FROM AUTHOR]

In current study, in order to find the control of general uncertain nonlinear systems, a new optimal hybrid control approach called Optimal General Type II Fuzzy Sliding Mode (OGT2FSM) is presented. In order to estimate unknown nonlinear activities in monitoring dynamic uncertainties, the benefits of general type‐2 fuzzy logic systems (GT2FLS) is utilized by the suggested controller. The suggested controller not only warranties the constancy and hardiness against uncertainties of the lumped resulted by external disturbances and un‐modeled dynamics, but also considerably decreases the control chattering inherent in traditional sliding mode control. Moreover, the Modified Backtracking Search Algorithm (MBSA), which is a new heuristic algorithm, is used in the offered controller. A comparison is performed between the results of current study and the results of some of the most recent studies on the same topic, which are an Adaptive Interval Type‐2 Fuzzy Logic Controller (AGT2FLC) and Conventional Sliding Mode Controller (CSMC), to assess the efficiency of the suggested controller. The suggested control scheme is finally used to the Electric Vehicles type as a case study. Results of simulation confirm the good performance the suggested controller. [ABSTRACT FROM AUTHOR]